Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "16" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 56 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 53 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459871 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.794629 | 0.013554 | -0.020984 | -0.822974 | -0.591755 | -0.042527 | 3.075640 | 2.593967 | 0.7067 | 0.6789 | 0.3784 | nan | nan |
| 2459870 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.184594 | 2.704884 | 0.253935 | -0.601619 | 0.842075 | 1.973090 | 3.909175 | 4.775845 | 0.7082 | 0.6762 | 0.3893 | nan | nan |
| 2459869 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.694798 | 0.029567 | 0.818200 | -0.544527 | 0.525960 | 0.119873 | 1.723637 | 0.030106 | 0.7178 | 0.7029 | 0.3744 | nan | nan |
| 2459868 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.422411 | 1.090735 | -0.865019 | -0.602967 | -0.502261 | 0.329920 | 3.798340 | 3.574743 | 0.7011 | 0.6767 | 0.3947 | nan | nan |
| 2459867 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.809494 | 1.129737 | -0.525076 | -0.466888 | 0.155573 | 1.347119 | 1.628355 | 3.473836 | 0.7129 | 0.6778 | 0.3961 | nan | nan |
| 2459866 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.661138 | 1.444650 | -0.263098 | -0.338447 | 0.332823 | 0.943769 | 1.379890 | 2.276557 | 0.7126 | 0.6816 | 0.3864 | nan | nan |
| 2459865 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.456716 | 1.436148 | -1.259163 | 0.622404 | -0.200366 | 0.697524 | 1.523594 | 2.957048 | 0.7407 | 0.7082 | 0.3586 | nan | nan |
| 2459864 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.542908 | 1.641913 | 2.247648 | 1.668324 | 0.776595 | 1.043723 | 3.602520 | 7.824933 | 0.7080 | 0.6732 | 0.4097 | nan | nan |
| 2459863 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.692787 | -0.306849 | 0.974983 | 0.956137 | -0.163247 | -0.573591 | 1.698513 | 2.190796 | 0.6992 | 0.6637 | 0.4009 | nan | nan |
| 2459862 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.423183 | 0.704929 | 1.982147 | 1.384340 | 0.113383 | 0.708232 | 0.992936 | 3.711667 | 0.6824 | 0.6913 | 0.4106 | nan | nan |
| 2459861 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.200353 | -0.440607 | 0.897828 | 1.040866 | -0.622815 | -0.169106 | 0.789205 | 2.179860 | 0.7180 | 0.6781 | 0.4094 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.465617 | -0.223390 | 1.253082 | 0.631237 | 0.573628 | 0.301193 | 0.884227 | 1.831830 | 0.7246 | 0.6752 | 0.4099 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.081316 | -0.676133 | 0.796343 | 0.878848 | -0.749724 | -0.529795 | 0.586486 | 1.755309 | 0.7265 | 0.6797 | 0.4077 | nan | nan |
| 2459858 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.965019 | -0.472015 | 0.903029 | 0.906812 | -0.564630 | -0.514551 | 0.727568 | 2.805525 | 0.7378 | 0.6844 | 0.4202 | 1.881635 | 1.539139 |
| 2459857 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.491715 | -0.858996 | 0.349332 | 0.302862 | 0.276692 | 0.746496 | 0.266292 | 0.105800 | 0.0250 | 0.0247 | 0.0005 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.57% | -1.270167 | 0.642305 | 0.799817 | 0.071514 | 0.536678 | 0.927209 | 1.831957 | 2.025990 | 0.7291 | 0.6991 | 0.4076 | 1.914500 | 1.528863 |
| 2459855 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 4.58% | 0.00% | -1.332394 | 1.599553 | 0.923619 | 0.157321 | 0.565512 | 1.178235 | 0.620610 | 1.125406 | 0.7091 | 0.7087 | 0.4389 | 1.540139 | 1.365097 |
| 2459854 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.93% | 0.00% | -1.584033 | 1.751094 | 0.253747 | -0.334832 | 0.366840 | 0.998526 | 0.866720 | 2.842071 | 0.7260 | 0.7384 | 0.4415 | 1.766856 | 1.461146 |
| 2459853 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -1.016983 | 0.348363 | 0.420435 | -0.190888 | 0.173201 | 0.464484 | 0.821602 | 2.334609 | 0.7539 | 0.6889 | 0.4290 | 1.844600 | 1.537672 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 4.86% | -1.215155 | -0.270533 | 0.681199 | 0.289843 | -0.685832 | 0.261936 | 0.677303 | 0.725340 | 0.8364 | 0.8336 | 0.2438 | 2.888955 | 2.689536 |
| 2459851 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 11.76% | 0.00% | -1.183048 | -0.157267 | 0.520520 | -0.033526 | -0.628900 | -0.650734 | 1.662543 | 2.363029 | 0.7774 | 0.7472 | 0.3319 | 1.907223 | 1.551982 |
| 2459850 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 18.02% | 0.00% | -0.938541 | 0.623896 | 0.304167 | -0.208133 | -0.859837 | 0.483950 | 1.255379 | 3.009023 | 0.7528 | 0.7508 | 0.3545 | 1.780249 | 1.473226 |
| 2459849 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.67% | 0.00% | -1.543382 | 0.404163 | 0.203114 | -0.685559 | 0.179755 | 0.973825 | 2.230743 | 2.560020 | 0.7521 | 0.7458 | 0.3622 | 1.653710 | 1.452708 |
| 2459848 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 30.15% | 0.00% | -0.945367 | 0.485743 | -0.973455 | -1.067534 | -1.008136 | 0.116463 | 0.524271 | 1.440540 | 0.7306 | 0.7477 | 0.3807 | 1.551403 | 1.427490 |
| 2459847 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.00% | -1.006954 | -0.019275 | -0.518975 | -0.724536 | 0.704831 | -0.000383 | 0.770236 | 1.505952 | 0.7355 | 0.6835 | 0.4343 | 1.719178 | 1.507868 |
| 2459846 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 33.33% | 0.00% | -0.753744 | -0.664870 | -0.078324 | -0.900401 | -0.565960 | 0.350472 | 0.979366 | 0.823748 | 0.8526 | 0.6842 | 0.4894 | 1.751752 | 1.491240 |
| 2459845 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.02% | 0.00% | -1.108130 | 1.240467 | -1.002444 | 0.095449 | 0.989761 | 1.298446 | 0.568966 | -0.053987 | 0.7510 | 0.7567 | 0.3675 | 1.231042 | 1.226116 |
| 2459844 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.904709 | -0.480445 | -0.917291 | 0.124699 | 1.184724 | -0.397176 | 0.050286 | -0.617501 | 0.0245 | 0.0241 | 0.0004 | nan | nan |
| 2459843 | digital_ok | 0.00% | 0.66% | 0.66% | 0.00% | 15.22% | 0.00% | -0.890046 | -0.001971 | -1.024649 | -1.191913 | -0.819698 | -0.373506 | 2.977496 | 0.111499 | 0.7570 | 0.7543 | 0.3809 | 1.933493 | 1.625236 |
| 2459842 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.075072 | -1.110969 | 0.169800 | 0.348361 | 0.308035 | 0.649416 | 1.866497 | 0.429727 | 0.7623 | 0.6551 | 0.2749 | 1.942841 | 1.769329 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 0.110044 | 0.411262 | -0.565121 | 0.061823 | 6.852922 | 1.899204 | 1.508892 | 0.784545 | 0.0247 | 0.0243 | 0.0006 | nan | nan |
| 2459840 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -1.967483 | -0.393088 | -0.319456 | -0.053811 | -0.685003 | -0.789584 | 0.346241 | 0.010017 | 0.0233 | 0.0231 | 0.0006 | nan | nan |
| 2459839 | digital_ok | 0.00% | - | - | - | - | - | -0.592595 | 1.054790 | -0.857324 | -0.042784 | 0.602820 | 3.445682 | 0.174703 | -0.456042 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -1.521372 | 0.699315 | -0.402073 | -0.953823 | -0.498111 | -0.325909 | 0.594692 | 1.514310 | 0.7470 | 0.6784 | 0.4211 | 2.109850 | 1.834640 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0344 | 0.0347 | 0.0012 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459833 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.917632 | -0.754900 | 0.103326 | -0.133086 | -0.695494 | 0.873074 | 0.540650 | -0.317196 | 0.0294 | 0.0315 | 0.0022 | nan | nan |
| 2459832 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.972361 | -1.280085 | -0.246997 | -1.063764 | 0.419379 | 1.180353 | 2.708424 | -0.091008 | 0.8084 | 0.5136 | 0.6046 | 1.676165 | 1.430993 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.631051 | 1.028792 | -1.107752 | -0.028552 | -0.244226 | -0.228640 | 0.224012 | -0.254115 | 0.0293 | 0.0368 | 0.0042 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.912744 | -1.241812 | -0.484865 | -1.181647 | -0.851417 | -0.402518 | 4.983458 | 2.144121 | 0.8031 | 0.4987 | 0.5978 | 4.898170 | 6.485498 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.478250 | 0.181846 | -0.555954 | -0.439591 | 0.162767 | 1.134113 | 5.928143 | 5.462129 | 0.7514 | 0.6397 | 0.4371 | 22.035343 | 12.696388 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.765583 | -0.601481 | -0.705208 | -0.546092 | -0.817320 | 0.147497 | 5.815147 | 12.592008 | 0.8019 | 0.5269 | 0.5626 | 5.170435 | 5.916994 |
| 2459827 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -1.524303 | -1.005866 | -0.708323 | -0.022723 | 0.036715 | 0.115181 | 1.346026 | 0.354552 | 0.7595 | 0.6482 | 0.4388 | 0.779297 | 0.639744 |
| 2459826 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.440484 | -1.038509 | -0.529779 | -0.358891 | -0.304103 | 0.551256 | 6.093559 | 1.150376 | 0.7983 | 0.5419 | 0.5379 | 10.412854 | 14.657204 |
| 2459825 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.309448 | -1.280002 | -0.020491 | -0.994773 | 8.805618 | 8.725483 | 3.698330 | 2.462638 | 0.7956 | 0.5468 | 0.5385 | 3.355055 | 2.308965 |
| 2459824 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.362613 | 0.621176 | 0.085369 | -0.942937 | 4.767340 | 5.140215 | 6.539801 | 7.427482 | 0.7012 | 0.6774 | 0.4145 | 7.738011 | 9.775218 |
| 2459823 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.027864 | -0.994688 | -0.312208 | -0.792135 | 0.056907 | -0.827901 | 3.600494 | 0.686723 | 0.7605 | 0.6029 | 0.4980 | 2.448673 | 2.551248 |
| 2459822 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.161230 | -0.760581 | -0.493300 | -0.486329 | -0.975565 | -1.072507 | 3.242218 | 2.107408 | 0.8020 | 0.5816 | 0.5330 | 1.874493 | 1.540542 |
| 2459821 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.435090 | -0.430572 | -0.558437 | -0.329077 | -0.224925 | -0.055251 | 1.255055 | 1.291155 | 0.7943 | 0.6011 | 0.5216 | 2.247563 | 1.854114 |
| 2459820 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -1.121030 | -0.149743 | -0.823307 | -0.095300 | 0.323064 | 2.118267 | 3.244709 | 2.542838 | 0.7779 | 0.6702 | 0.4385 | 2.122770 | 1.743482 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.243510 | -0.415679 | -0.535232 | -0.592636 | -0.127735 | -0.471174 | 1.644526 | 2.615462 | 0.8103 | 0.6562 | 0.5250 | 2.238718 | 1.981082 |
| 2459816 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.700800 | -1.318322 | -0.098189 | -1.279848 | -0.096780 | -0.306051 | 9.570347 | 7.365016 | 0.8467 | 0.5894 | 0.5968 | 3.905188 | 4.589187 |
| 2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.190125 | -1.207350 | -0.329792 | -1.158658 | -1.034274 | -1.346651 | 3.129830 | 1.394306 | 0.7966 | 0.6594 | 0.5287 | 2.394434 | 2.140082 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 4.775845 | -0.184594 | 2.704884 | 0.253935 | -0.601619 | 0.842075 | 1.973090 | 3.909175 | 4.775845 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 1.723637 | -0.694798 | 0.029567 | 0.818200 | -0.544527 | 0.525960 | 0.119873 | 1.723637 | 0.030106 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 3.798340 | -0.422411 | 1.090735 | -0.865019 | -0.602967 | -0.502261 | 0.329920 | 3.798340 | 3.574743 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 3.473836 | -0.809494 | 1.129737 | -0.525076 | -0.466888 | 0.155573 | 1.347119 | 1.628355 | 3.473836 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.276557 | 1.444650 | -0.661138 | -0.338447 | -0.263098 | 0.943769 | 0.332823 | 2.276557 | 1.379890 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.957048 | -1.456716 | 1.436148 | -1.259163 | 0.622404 | -0.200366 | 0.697524 | 1.523594 | 2.957048 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 7.824933 | 1.641913 | -1.542908 | 1.668324 | 2.247648 | 1.043723 | 0.776595 | 7.824933 | 3.602520 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.190796 | -1.692787 | -0.306849 | 0.974983 | 0.956137 | -0.163247 | -0.573591 | 1.698513 | 2.190796 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 3.711667 | -1.423183 | 0.704929 | 1.982147 | 1.384340 | 0.113383 | 0.708232 | 0.992936 | 3.711667 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.179860 | -0.440607 | -1.200353 | 1.040866 | 0.897828 | -0.169106 | -0.622815 | 2.179860 | 0.789205 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.831830 | -1.465617 | -0.223390 | 1.253082 | 0.631237 | 0.573628 | 0.301193 | 0.884227 | 1.831830 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.755309 | -1.081316 | -0.676133 | 0.796343 | 0.878848 | -0.749724 | -0.529795 | 0.586486 | 1.755309 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.805525 | -0.472015 | -0.965019 | 0.906812 | 0.903029 | -0.514551 | -0.564630 | 2.805525 | 0.727568 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Variability | 0.746496 | -0.858996 | -0.491715 | 0.302862 | 0.349332 | 0.746496 | 0.276692 | 0.105800 | 0.266292 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.025990 | -1.270167 | 0.642305 | 0.799817 | 0.071514 | 0.536678 | 0.927209 | 1.831957 | 2.025990 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Shape | 1.599553 | 1.599553 | -1.332394 | 0.157321 | 0.923619 | 1.178235 | 0.565512 | 1.125406 | 0.620610 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.842071 | 1.751094 | -1.584033 | -0.334832 | 0.253747 | 0.998526 | 0.366840 | 2.842071 | 0.866720 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.334609 | 0.348363 | -1.016983 | -0.190888 | 0.420435 | 0.464484 | 0.173201 | 2.334609 | 0.821602 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 0.725340 | -1.215155 | -0.270533 | 0.681199 | 0.289843 | -0.685832 | 0.261936 | 0.677303 | 0.725340 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.363029 | -1.183048 | -0.157267 | 0.520520 | -0.033526 | -0.628900 | -0.650734 | 1.662543 | 2.363029 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 3.009023 | -0.938541 | 0.623896 | 0.304167 | -0.208133 | -0.859837 | 0.483950 | 1.255379 | 3.009023 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.560020 | -1.543382 | 0.404163 | 0.203114 | -0.685559 | 0.179755 | 0.973825 | 2.230743 | 2.560020 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.440540 | 0.485743 | -0.945367 | -1.067534 | -0.973455 | 0.116463 | -1.008136 | 1.440540 | 0.524271 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.505952 | -0.019275 | -1.006954 | -0.724536 | -0.518975 | -0.000383 | 0.704831 | 1.505952 | 0.770236 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 0.979366 | -0.753744 | -0.664870 | -0.078324 | -0.900401 | -0.565960 | 0.350472 | 0.979366 | 0.823748 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Variability | 1.298446 | 1.240467 | -1.108130 | 0.095449 | -1.002444 | 1.298446 | 0.989761 | -0.053987 | 0.568966 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Variability | 1.184724 | -0.904709 | -0.480445 | -0.917291 | 0.124699 | 1.184724 | -0.397176 | 0.050286 | -0.617501 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 2.977496 | -0.001971 | -0.890046 | -1.191913 | -1.024649 | -0.373506 | -0.819698 | 0.111499 | 2.977496 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 1.866497 | -0.075072 | -1.110969 | 0.169800 | 0.348361 | 0.308035 | 0.649416 | 1.866497 | 0.429727 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Variability | 6.852922 | 0.110044 | 0.411262 | -0.565121 | 0.061823 | 6.852922 | 1.899204 | 1.508892 | 0.784545 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 0.346241 | -1.967483 | -0.393088 | -0.319456 | -0.053811 | -0.685003 | -0.789584 | 0.346241 | 0.010017 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Variability | 3.445682 | 1.054790 | -0.592595 | -0.042784 | -0.857324 | 3.445682 | 0.602820 | -0.456042 | 0.174703 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.514310 | 0.699315 | -1.521372 | -0.953823 | -0.402073 | -0.325909 | -0.498111 | 1.514310 | 0.594692 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Variability | 0.873074 | -0.754900 | -0.917632 | -0.133086 | 0.103326 | 0.873074 | -0.695494 | -0.317196 | 0.540650 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 2.708424 | -0.972361 | -1.280085 | -0.246997 | -1.063764 | 0.419379 | 1.180353 | 2.708424 | -0.091008 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Shape | 1.028792 | -0.631051 | 1.028792 | -1.107752 | -0.028552 | -0.244226 | -0.228640 | 0.224012 | -0.254115 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 4.983458 | -0.912744 | -1.241812 | -0.484865 | -1.181647 | -0.851417 | -0.402518 | 4.983458 | 2.144121 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 5.928143 | 0.181846 | -1.478250 | -0.439591 | -0.555954 | 1.134113 | 0.162767 | 5.462129 | 5.928143 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 12.592008 | -0.601481 | -0.765583 | -0.546092 | -0.705208 | 0.147497 | -0.817320 | 12.592008 | 5.815147 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 1.346026 | -1.524303 | -1.005866 | -0.708323 | -0.022723 | 0.036715 | 0.115181 | 1.346026 | 0.354552 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 6.093559 | -1.038509 | -0.440484 | -0.358891 | -0.529779 | 0.551256 | -0.304103 | 1.150376 | 6.093559 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Variability | 8.805618 | -1.280002 | -0.309448 | -0.994773 | -0.020491 | 8.725483 | 8.805618 | 2.462638 | 3.698330 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 7.427482 | -1.362613 | 0.621176 | 0.085369 | -0.942937 | 4.767340 | 5.140215 | 6.539801 | 7.427482 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 3.600494 | -0.994688 | 0.027864 | -0.792135 | -0.312208 | -0.827901 | 0.056907 | 0.686723 | 3.600494 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 3.242218 | -0.161230 | -0.760581 | -0.493300 | -0.486329 | -0.975565 | -1.072507 | 3.242218 | 2.107408 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 1.291155 | -0.430572 | 0.435090 | -0.329077 | -0.558437 | -0.055251 | -0.224925 | 1.291155 | 1.255055 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 3.244709 | -1.121030 | -0.149743 | -0.823307 | -0.095300 | 0.323064 | 2.118267 | 3.244709 | 2.542838 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Temporal Discontinuties | 2.615462 | -0.243510 | -0.415679 | -0.535232 | -0.592636 | -0.127735 | -0.471174 | 1.644526 | 2.615462 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 9.570347 | -1.318322 | -0.700800 | -1.279848 | -0.098189 | -0.306051 | -0.096780 | 7.365016 | 9.570347 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | ee Temporal Discontinuties | 3.129830 | -1.207350 | -0.190125 | -1.158658 | -0.329792 | -1.346651 | -1.034274 | 1.394306 | 3.129830 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16 | N01 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |